Handling uncertainty in agricultural supply chain management: A state of the art

被引:174
作者
Borodin, Valeria [1 ,2 ,3 ]
Bourtembourg, Jean [2 ]
Hnaien, Faicel [3 ]
Labadie, Nacima [3 ]
机构
[1] CNRS, CMP Georges Charpak, Ecole Mines St Etienne, LIMOS,UMR 6158, F-13541 Gardanne, France
[2] Ind Zone Villette, Agr Cooperat Soc Reg Arcis Sur Aube SCARA, F-10700 Villette Sur Aube, France
[3] Univ Technol Troyes, Charles Delaunay Inst ICD, Lab Ind Syst Optimizat LOSI, ICD LOSI, 12 Rue Marie Curie CS 42060, F-10004 Troyes, France
关键词
OR in agriculture; State of the art; Uncertainty modeling; Supply chain management; WATER-QUALITY MANAGEMENT; DISCRETE-EVENT SIMULATION; DECISION-SUPPORT-SYSTEM; ROBUST OPTIMIZATION; OPERATIONS-RESEARCH; PROGRAMMING-MODEL; FARMING SYSTEMS; RISK-MANAGEMENT; NETWORK DESIGN; FUZZY;
D O I
10.1016/j.ejor.2016.03.057
中图分类号
C93 [管理学];
学科分类号
12 ; 1201 ; 1202 ; 120202 ;
摘要
Given the evolution in the agricultural sector and the new challenges it faces, managing agricultural supply chains efficiently has become an attractive topic for researchers and practitioners. Against this background, the integration of uncertain aspects has continuously gained importance for managerial decision making since it can lead to an increase in efficiency, responsiveness, business integration, and ultimately in market competitiveness. In order to capture appropriately the uncertain conjuncture of most agricultural real-life applications, an increasing amount of research effort is especially dedicated to treating uncertainty. In particular, quantitative modeling approaches have found extensive use in agricultural supply chain management. This paper provides an overview of the latest advances and developments in the application of operations research methodologies to handling uncertainty occurring in the agricultural supply chain management problems. It seeks to: (i) offer a representative overview of the predominant research topics, (ii) highlight the most pertinent and widely used frameworks, and (iii) discuss the emergence of new operations research advances in the agricultural sector. The broad spectrum of reviewed contributions is classified and presented with respect to three most relevant discerned features: uncertainty modeling types, programming approaches, and functional application areas. Ultimately, main review findings are pointed out and future research directions which emerge are suggested. (C) 2016 Elsevier B.V. All rights reserved.
引用
收藏
页码:348 / 359
页数:12
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